RETINA FUNDUS IMAGE MASK GENERATION USING PSEUDO PARAMETRIC MODELING TECHNIQUE

Abstract

The use of vascular intersection as one of the symptoms
for monitoring and diagnosis of diabetic retinopathy from
fundus images have been widely reported in literatures. In
this work, a new hybrid approach that makes use of three
different methods of vascular intersection detection namely
Modified cross-point number (MCN), Combine Cross Points
(CNN) and Artificial Neural Network (ANN) is hereby proposed.
Result obtained from the application of this technique
to both simulated and experimental shows a very high accuracy
and precision value in detecting both bifurcation and
cross over points. Thus an improvement in bifurcation and
vascular point detection and a good tool in the monitoring
and diagnosis of diabetic retinopathy.